Requirements:

Proven experience leading and contributing hands-on to AI/ML engineering and operations in large-scale production environments.
Deep understanding of AI model lifecycle management, distributed systems, and integration of applications powered by artificial intelligence into customer-facing platforms.
Strong software engineering background with experience in Java or JVM-based environments, along with modern AI/ML frameworks and data pipelines.
Expertise in CI/CD pipelines, infrastructure-as-code (IaC), containerized environments, and cloud-native architectures.
Experience with monitoring, logging, alerting systems, and operational automation, including building self-healing and highly available systems.
Demonstrated leadership capability in guiding multidisciplinary teams and collaborating effectively across engineering, research, and product organizations.

What You'll Be Doing:

Define and implement the strategic roadmap for AI Engineering, aligning technical direction with broader AI and business objectives.
Architect, design, and optimize scalable AI systems that operate reliably in high-throughput, production environments.
Lead end-to-end operationalization of AI/ML models, ensuring robust lifecycle management including deployment, monitoring, and iteration.
Drive automation, CI/CD, and infrastructure-as-code best practices to improve system scalability, resilience, and performance.
Establish operational excellence frameworks, including monitoring, incident response, root cause analysis, and performance optimization.
Build and mentor a high-performing, multidisciplinary team while fostering a culture of innovation, accountability, and shared ownership.